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The Cult of Statistical Significance shows, field by field, how "statistical significance," a technique that dominates many sciences, has been a huge mistake. The authors find that researchers in a broad spectrum of fields, from agronomy to zoology, employ testing that doesn't "test" and estimating that doesn't "estimate". The facts will startle the outside reader: how could a group of brilliant scientists wander so far from scientific magnitudes? This study will encourage scientists who want to know how to get the statistical sciences back on track and fulfill their quantitative promise. The book shows for the first time how wide the disaster is, and how bad for science, and it traces the problem to its historical, sociological, and philosophical roots.Read more...

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A significant problem --
Dieting "significance" and the case of Vioxx --
The sizeless stare of statistical significance --
What the sizeless scientists say in defense --
Better practice: [beta]-importance vs. [alpha]-"significance" --
A lot can go wrong in the use of significance tests in economics --
A lot did go wrong in the American Economic Review during the 1980s --
Is economic practice improving? --
How big is big in economics? --
What the sizeless stare costs, economically speaking --
How economics stays that way: the textbooks and the referees --
The not-boring rise of significance in psychology --
Psychometrics lacks power --
The psychology of psychological significance testing --
Medicine seeks a magic pill --
Rothman's revolt --
On drugs, disability, and death --
Edgeworth's significance --
"Take 3[sigma] as definitely significant": Pearson's rule --
Who sits on the egg of culculus canorus? Not Karl Pearson --
Gosset: the fable of the bee --
Fisher: the fable of the wasp --
How the wasp stung the bee and took over some sciences --
Eighty years of trained incapacity: how such a thing could happen --
What to do.

Abstract:

Null hypothesis significance testing is in other words a scientific train-wreck, about which a small group of statisticians have been warning. This book shows how the wreck happened, and reports on the fatalities. It shows how wide the disaster is, and traces the problem to its historical, sociological, and philosophical roots.Read more...

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Editorial reviews

Publisher Synopsis

"[Steve Ziliak and Deirdre McCloskey] explain to us why the misunderstanding of statistical significance has lead to bad government policy making and how one particularly famous brewery employed the technique to improve the pints we enjoy today."--Tim Harford, BBC --Tim Harford"BBC" (01/23/2009) "What is important is a shift of emphasis away from a dichotomous world of true and false towards a recognition of "oomph." This is what the presented book tries to achieve. It is also fun to read, rich with historical information and an excellent reminder of what empirical work of any sort is all about."--Walter Kramer, Stat Papers--W. Kramer "Stat Papers " "The book is a model of scholarship, transparent in its method, wide-reaching in its disciplinary expertise, and highly literate, including occasional haiku poems and humor such as, 'If the variable doesn't fit/you may not have to acquit.' The authors convincingly argue that environmental quality, jobs, and even lives are at stake."--M. H./i> --M. H. Maier"Choice" (10/21/2009) "If not Fisherian significance, what should be the Holy Grail of statistics? Ziliak and McCloskey . . . answer: "Oomph." We should identify quantities that matter and measure them, not merely determine whether they can be distinguished from the null (meaning no effect) at some predetermined likelihood level. The validity of this point I take to be virtually self-evident. Yet statistical tests that ignore quantity remain pervasive, as the authors demonstrate through quantitative analyses of the contents of some very prestigious journals of economics, psychology, and medicine."--Theodore Porter, Science --Theodore Porter"Science" (06/05/2009) "A clear trade-off: how much confidence [in a result] is "enough" depends on the costs of further research and the benefits of extra precision. Ziliak and his co-author Deirdre McCloskey argue in The Cult of Statistical Significance that most academic disciplines have forgotten this trade-off . . . A sharp line for statistical significance makes no sense, and it has a cost."--Tim Harford, The Financial Times --Tim Harford"Financial Times" (02/07/2009) "The Cult of Statistical Significance has virtues that extend beyond its core message. It is clearly written and should be accessible to those who have neither formal training in statistics nor a desire to secure any. It is full of examples that illustrate why it is the strength of relationships and not their statistical significance that mainly matters."--Richard Lempert, Law and Social Inquiry --Richard Lempert"Law and Social Inquiry" (01/01/2009) "Persuading professionals that their procedures are wrong is a long and lonely task. McCloskey, joined later by Ziliak, has been conducting such a crusade against the misuse of significance testing for over 25 years. This book presents their argument, gives lots of examples of the adverse consequences of misuse, and provides some history of the controversy, which dates from the origins of mathematical statistics."--Ron P./i> --Ron P. Smith"Journal of Economic Issues" (01/01/2009) "Despite appearing to be a book of limited appeal - it is after all a book that looks at a set of statistical techniques - it is one that has immense social implications. We live in an age where ideologies have largely been cast aside and instead we are governed increasingly by a class of politicians and civil servants who aim for 'evidence-based' policy-making. When that evidence is based on statistically significant results that ignore any quantification of results then we all have reason to pay attention."--London Book Review --NA"London Book Review" (12/23/2008) ""The Cult of Statistical Significance" has virtues that extend beyond its core message. It is clearly written and should be accessible to those who have neither formal training in statistics nor a desire to secure any. It is full of examples that illustrate why it is the strength of relationships and not their statistical significance that mainly matters." Richard Lempert, "Law and Social Inquiry" --Richard Lempert"Law and Social Inquiry" (01/01/2009)"Read more...